class_docstr: Implementation of methods in Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks.
  Wang et al. (2019).
  
  | Paper link: https://people.cs.uchicago.edu/~ravenben/publications/pdf/backdoor-sp19.pdf
class_docstr_tok: ["Implementation","of","methods","in","Neural","Cleanse",":","Identifying","and","Mitigating","Backdoor","Attacks","in","Neural","Networks",".","Wang","et","al",".","(","2019",")",".","|","Paper","link",":","https",":","\/\/people.cs.uchicago.edu\/~ravenben\/publications\/pdf\/backdoor-sp19.pdf"]
docstr: Set the weights (and biases) of a neuron at index in the penultimate layer of the neural network to zero
  
  :param index: An index of the penultimate layer
docstr_tok: ["Set","the","weights","(","and","biases",")","of","a","neuron","at","index","in","the","penultimate","layer","of","the","neural","network","to","zero",":","param","index",":","An","index","of","the","penultimate","layer"]
code: def _prune_neuron_at_index(self, index: int) -> None:
      """
      Set the weights (and biases) of a neuron at index in the penultimate layer of the neural network to zero
  
      :param index: An index of the penultimate layer
      """
      raise NotImplementedError
  
file_path: adversarial-robustness-toolbox/art/estimators/poison_mitigation/neural_cleanse/neural_cleanse.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import Union, Tuple, List
  import numpy
  from art.estimators.certification.abstain import AbstainPredictorMixin
  from art.utils import to_categorical
label_desc: Use image node_id 5 for calling the NeuralCleanseMixin obj's underlying member method code with example usage: obj._prune_neuron_at_index(index) without return types